In human-robot interaction, natural language is one of the most desirable forms of communication between users and robots [1]}, [2]}. However, the interpretation of natural language remains an extremely hard problem for robots. One major issue is that even with the successful conversion of speech to text, there is still a considerable gap between text and its appropriate interpretation. One scenario where this issue exists is language-based robot navigation. Consider the map layout of an office in Fig. REF . If one wants the robot to deliver a document to meeting room 124, he/she would command differently depending on his/her knowledge about the office. If the user knows the exact room number “124”, he/she would say “Go to room 124”. Otherwise, the user might refer to the meeting room with respect to a nearby location, an alternative but very intuitive command would be “Go to the meeting room near the north exit.” Despite the tiny modification of the original command, it has already become non-trivial for robots to understand due to the reasoning required.
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